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Record W2324786653 · doi:10.1097/jom.0b013e3181f75f90

Strategic Wellness Management in Finland

2010· article· en· W2324786653 on OpenAlexaff
Ossi Aura, Guy Ahonen, Juhani Ilmarinen

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2010
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsInternational Submarine Engineering (Canada)
Fundersnot available
KeywordsScope (computer science)BusinessStrategic managementProductivityIndex (typography)Measure (data warehouse)MarketingProcess managementKnowledge managementOperations managementComputer scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

OBJECTIVES: To examine the scope of strategic wellness management (SWM) in Finland. To measure management of wellness a strategic wellness management index (SWMI) was developed. METHODS: On the basis of the developed SWM model an Internet questionnaire was conducted for randomly selected employers representing seven business areas and three size categories. Corporate activities and SWMI for each employer and for business area and size groups were calculated. RESULTS: Results highlighted relatively good activity in strategic wellness (SW) processes and fairly low level of SWM procedures. The average values (± SD) of SWMI were 53.6 ± 12.3 for large, 42.8 ± 11.7 for medium-size, and 32.8 ± 12.1 for small companies. CONCLUSIONS: SWMI can be a positive new, strong concept to measure SW processes and thus improve both the well-being of the employees and the productivity of the enterprise.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.374
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2010
Admission routes1
Has abstractyes

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